A structural health monitoring system has been installed in a typical Tibetan timber building to measure the structural strains. In this paper, the singular spectrum analysis (SSA) is used for both the long-term and short-term forecasting on the structural strain variations. The optimal parameters of the SSA are selected according to the minimum mean square error of the prediction. In the 3 months forecasting, sequential prediction of 1 month could be achieved with the best result. For the 1 day forecasting, the data length in the forecasting model should not be less than 10 days. Results show that the SSA method could effectively forecast the long-term trend and the short-term fluctuation of the strains. The SSA is found slightly superior for both the long-term and short-term forecasting compared with results from the autoregressive integrated moving average (ARIMA) model.

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